<?xml version="1.0" encoding="UTF-8" ?><OAI-PMH xmlns="http://www.openarchives.org/OAI/2.0/" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance" xsi:schemaLocation="http://www.openarchives.org/OAI/2.0/ http://www.openarchives.org/OAI/2.0/OAI-PMH.xsd"><responseDate>2026-10-14T15:59:30Z</responseDate><request identifier="10.48606/fTBvhsaGfoDmhOTV" metadataPrefix="oai_dc" verb="GetRecord">https://www.radar-service.eu/oai/OAIHandler</request><GetRecord><record><header><identifier>10.48606/fTBvhsaGfoDmhOTV</identifier><datestamp>2026-04-24T07:43:40Z</datestamp></header><metadata><oai_dc:dc xmlns:dc="http://purl.org/dc/elements/1.1/"
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   <dc:identifier>https://dx.doi.org/10.48606/fTBvhsaGfoDmhOTV</dc:identifier>
   <dc:creator>Steuer, Jakob</dc:creator>
   <dc:title>Molecular Dynamics Simulation Data and Analysis Workflow for Studying Bivalent Ligand Binding to the Guanidine-II Riboswitch</dc:title>
   <dc:publisher>University of Konstanz</dc:publisher>
   <dc:date>2024</dc:date>
   <dc:subject>Chemistry</dc:subject>
   <dc:type>dataset</dc:type>
   <dc:subject>Simulation Setup Files, Simulation Data, Jupyter Notebook</dc:subject>
   <dc:subject>Dataset</dc:subject>
   <dc:source>Molecular Dynamics Simulations</dc:source>
   <dc:source>Other</dc:source>
   <dc:rights>info:eu-repo/semantics/openAccess</dc:rights>
   <dc:rights>https://creativecommons.org/licenses/by/4.0/legalcode</dc:rights>
   <dc:contributor>Sinn, Malte</dc:contributor>
   <dc:contributor>Eble, Franziska</dc:contributor>
   <dc:contributor>Rütschlin, Sina</dc:contributor>
   <dc:contributor>Böttcher, Thomas</dc:contributor>
   <dc:contributor>Hartig, Jörg S.</dc:contributor>
   <dc:contributor>Peter, Christine</dc:contributor>
   <dc:description> The underlying study focused on ligand binding of bivalent ligands to the guanidine-II riboswitch. The dataset was generated using MD simulations and Machine Learning (ML) algorithms and contains the following directories and data:  1. simulation_data: Molecular Dynamics (MD) simulation trajectory data to replicate the analysis presented in the associated publication. 2. processed_data: Python code, a Python coding environment file, and a processed data file to replicate the dimensionality reduction and clustering workflow used in the associated publication. 3. sim_prep_example: Setup data and force field files to replicate the corresponding MD simulation data. See the README file for a more detailed description of content and technical instructions for this dataset. </dc:description>
   <dc:subject>RNA</dc:subject>
   <dc:subject>Riboswitch</dc:subject>
   <dc:subject>Guanidinium</dc:subject>
   <dc:subject>MD Simulation</dc:subject>
   <dc:subject>Molecular Dynamics</dc:subject>
   <dc:subject>Ligand Binding</dc:subject>
   <dc:subject>in vivo study</dc:subject>
   <dc:subject>Machine Learning</dc:subject>
   <dc:subject>Clustering</dc:subject>
   <dc:subject>Dimensionality Reduction</dc:subject>
   <dc:contributor>Sinn, Malte</dc:contributor>
   <dc:contributor>Eble, Franziska</dc:contributor>
   <dc:contributor>Rütschlin, Sina</dc:contributor>
   <dc:contributor>Böttcher, Thomas</dc:contributor>
   <dc:contributor>Hartig, Jörg S.</dc:contributor>
   <dc:contributor>Peter, Christine</dc:contributor>
   <dc:language>eng</dc:language>
   <dc:relation>10.1093/nargab/lqae132</dc:relation>
   <dc:relation>https://ror.org/018mejw64</dc:relation>
   <dc:relation>(KoRS-CB)</dc:relation>
   <dc:format>application/x-tar</dc:format>
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